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Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

Advanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee, Oliver James, Gaeun Jung, Doyun Lee, Yee‐Joon Kim   +4 more
wiley   +1 more source

Identifying maximally informative signal-aware representations of single-cell data using the Information Bottleneck

Dubnov S, Piran Z, Alper A, Yefroimsky A, Soreq H, Nitzan M.   +5 more
europepmc   +1 more source

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A Survey on Information Bottleneck

IEEE Transactions on Pattern Analysis and Machine Intelligence
This survey is for the remembrance of one of the creators of the information bottleneck theory, Prof. Naftali Tishby, passing away at the age of 68 on August, 2021. Information bottleneck (IB), a novel information theoretic approach for pattern analysis and representation learning, has gained widespread popularity since its birth in 1999.
Shizhe Hu, Zhengzheng Lou, Xiaoqiang Yan, Yangdong Ye   +3 more
openaire   +4 more sources

Information Bottleneck and Aggregated Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
We consider the problem of learning a neural network classifier. Under the information bottleneck (IB) principle, we associate with this classification problem a representation learning problem, which we call "IB learning". We show that IB learning is, in fact, equivalent to a special class of the quantization problem.
Soflaei, Masoumeh, Zhang, Richong, Guo, Hongyu, Al-Bashabsheh, Ali, Mao, Yongyi   +4 more
openaire   +2 more sources

A Spiking Neuron as Information Bottleneck

Neural Computation, 2010
Neurons receive thousands of presynaptic input spike trains while emitting a single output spike train. This drastic dimensionality reduction suggests considering a neuron as a bottleneck for information transmission. Extending recent results, we propose a simple learning rule for the weights of spiking neurons derived from the information bottleneck (
Buesing L., Maass W.
openaire   +2 more sources

Information Bottleneck Problem Revisited

2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2019
In this paper, we revisit the information bottleneck problem whose formulation and solution are of great importance in both information theory and statistical learning applications. We go into details as to why the problem was first introduced and how the algorithm proposed using Lagrangian method to solve such problems fell short of an exact solution.
Farhang Bayat, Shuangqing Wei
openaire   +1 more source

Neural Information Bottleneck Decoding

2020 14th International Conference on Signal Processing and Communication Systems (ICSPCS), 2020
Receiver-sided channel decoding is a crucial, but computationally very demanding task. Recently, information-bottleneck-based decoding received considerable attention in the literature, as it achieves very good performance with coarse quantization and low complexity.
Stark, Maximilian, Lewandowsky, Jan, Bauch, Gerhard   +2 more
openaire   +1 more source

Distributed cooperative information bottleneck

2017 IEEE International Symposium on Information Theory (ISIT), 2017
This paper investigates a scenario where two distant nodes separately observe memoryless process, namely X 1 and X 2 , and can cooperate through multiple exchanges of messages with the goal of enabling a third node to learn “relevant information” (measured in terms of a multi-letter mutual information) about some hidden memoryless process Y, which is ...
Vera, Matias, Vega, Leonardo Rey, Piantanida, Pablo   +2 more
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The two-way cooperative Information Bottleneck

2015 IEEE International Symposium on Information Theory (ISIT), 2015
The two-way Information Bottleneck problem, where two nodes exchange information iteratively about two arbitrarily dependent memoryless sources, is considered. Based on the observations and the information exchange, each node is required to extract “relevant information”, measured in terms of the normalized mutual information, from two arbitrarily ...
Matias, Vera, Rey Vega, Leonardo, Piantanida, Pablo   +2 more
openaire   +2 more sources

Contrastive Learning via Variational Information Bottleneck

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recent advances in self-supervised learning have witnessed great achievements, especially with the introduction of contrastive learning, where the goal is to maximize the mutual information between different augmentations of the same image, i.e., positive pairs. However, such optimization does not necessarily correspond to optimal representation due to
Jin Li, Yaoming Wang, Xiaopeng Zhang, Dongsheng Jiang, Wenrui Dai, Chenglin Li, Hongkai Xiong, Qi Tian   +7 more
openaire   +2 more sources